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REVIEW OF THE IMPACT OF ARTIFICIAL INTELLIGENCE ON PROJECT MANAGEMENT PRACTICES: INSIGHTS FROM INDUSTRY EXPERTS IN GHANA

dc.contributor.authorOtoo, Daniel
dc.contributor.copyright-releaseNot Applicable
dc.contributor.degreeMaster of Science
dc.contributor.departmentBusiness
dc.contributor.ethics-approvalNot Applicable
dc.contributor.external-examinerNA
dc.contributor.manuscriptsNot Applicable
dc.contributor.thesis-readerJoyline Makani, PhD
dc.contributor.thesis-readerPaola Gonzalez, PhD
dc.contributor.thesis-supervisorKyung Young Lee, PhD
dc.date.accessioned2026-01-06T17:09:22Z
dc.date.available2026-01-06T17:09:22Z
dc.date.defence2025-12-11
dc.date.issued2026-01-05
dc.description.abstractAdvancements in artificial intelligence (AI) are reshaping organizational operations and strategic decision-making, with significant implications for project management (PM). As a core organizational function, PM plays a pivotal role in achieving corporate objectives through the successful execution of projects. The integration of AI into PM processes offers opportunities to enhance efficiency, optimize resource allocation, and improve decision-making. Despite growing scholarly interest, existing literature lacks a comprehensive framework that holistically examines AI’s influence across PM knowledge areas, process groups, and performance domains. Furthermore, methodological limitations persist, as prior studies predominantly employ singular approaches such as systematic literature reviews (SLRs) or quantitative surveys, while qualitative insights remain underexplored. Addressing these gaps, this study adopts a mixed-methods approach, combining an SLR with key informant interviews (KIIs) of industry professionals in Ghana—a region underrepresented in current research yet notable for its advancements in ICT adoption. Guided by the Task-Technology Fit (TTF) model and the Technology-Organization-Environment (TOE) framework, the SLR synthesizes findings from six reputable databases on the impact of AI on the project management body of knowledge (PMBOK) Guide, while KIIs provide contextual insights into practical challenges and opportunities. The research seeks to answer two primary questions: (1) How do AI-driven tools and techniques influence PM practices, including principles, process groups, and performance measures? (2) What challenges arise in implementing AI within PM in Ghana, Africa? Findings are expected to contribute theoretical and practical perspectives, offering actionable recommendations for organizations and future research directions (with four propositions). This study underscores AI’s transformative potential in PM and highlights the need for integrative frameworks to guide its effective adoption.
dc.identifier.urihttps://hdl.handle.net/10222/85596
dc.language.isoen
dc.subjectArtificial Intelligence
dc.subjectProject Management
dc.titleREVIEW OF THE IMPACT OF ARTIFICIAL INTELLIGENCE ON PROJECT MANAGEMENT PRACTICES: INSIGHTS FROM INDUSTRY EXPERTS IN GHANA

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